Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/runtimenoteslabs/memory-layer/recallgit clone --depth 1 https://github.com/runtimenoteslabs/memory-layerWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00012 | $0.00430 |
| Opus 5 | $0.00006 | $0.00215 |
| Sonnet 5 | $0.00002 | $0.00086 |
| Haiku 4.5 | $0.00001 | $0.00043 |
Grade A, and why
recall scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Recall Command
Explicitly search the Memory Layer for relevant memories. Note that Agent Skills usually handle retrieval automatically based on conversation context, so this command is rarely needed.
Usage
/recall <query> [--limit N] [--category <cat>]
Options
| Option | Description | Default |
|---|---|---|
--limit N |
Maximum number of results | 5 |
--category <cat> |
Filter by category | all |
--min-score <float> |
Minimum outcome score | -1.0 |
Examples
# Search for authentication patterns
/recall "authentication patterns"
# Search with limit
/recall "database connection" --limit 10
# Search within a category
/recall "naming" --category convention
# Search for high-confidence memories only
/recall "error handling" --min-score 0.3
Implementation
Search memories and display results:
mem search "$QUERY" --format context --limit 5
When to Use
The memory-retrieval Agent Skill automatically retrieves memories when you:
- Ask about past decisions ("what did we decide about...")
- Reference conventions ("what's our convention for...")
- Mention previous work ("last time we...", "we discussed...")
Use /recall explicitly when:
- You want to browse all memories on a topic
- You need more results than auto-retrieval provides
- You want to filter by specific category or score
- Auto-retrieval didn't surface what you were looking for
Result Format
Results are ranked by a hybrid score combining:
- Semantic similarity (35%)
- Outcome score (25%) - proven advice ranks higher
- Recency (15%)
- Frequency of use (15%)
- Confidence (10%)
After reviewing results, use /outcome <id> worked|failed|partial to provide feedback.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 71 lines · 12 tokens per session scan A c2b1163d8a59
recall is a command published in the GitHub repository runtimenoteslabs/memory-layer (10 stars, last pushed 3mo ago), licensed MIT. It adds 12 tokens to every session and 430 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
memory-status
Check the Pseudolife-MCP memory daemon and report bank health.
dream
Copy to .claude/commands/dream.md in any project to get /dream. -->.
projects
View your Claude Code projects tracked by EverMem.
evolve-lite-subscribe
Add a shared guidelines repo (read-scope subscription or write-scope publish target) to the unified repos list.
image-node-intake
Parse a visual brief into the Image Node Factory intake JSON.
graphify
Turn your vault into a clustered knowledge graph with HTML and JSON outputs.